Policy Headline Interpreter Skill

Organization

Wind-Alice

policy_headline_interpreter_skill

解读政策新闻对行业、题材和个股的影响路径、受益方向与执行不确定性，帮助区分真正政策催化与噪音扰动。适用于政策密集期、新闻快判与板块机会识别。

Overview

Publisher	Wind-Alice
Repository	`AliceMarket`
Skill name	`policy_headline_interpreter_skill`
Stars	135
Forks	18
Bundled files	Instructions only
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by Wind-Alice on GitHub. Read the source before you install it.

Installation

Install the Policy Headline Interpreter Skill AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Wind-Alice/AliceMarket/tree/main/skills/policy_headline_interpreter_skill
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/Wind-Alice/AliceMarket/tree/main/skills/policy_headline_interpreter_skill

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/Wind-Alice/AliceMarket.git /tmp/AliceMarket
mkdir -p .claude/skills
cp -r /tmp/AliceMarket/skills/policy_headline_interpreter_skill .claude/skills/policy_headline_interpreter_skill

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Policy Headline Interpreter Skill in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Policy Headline Interpreter Skill on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Policy Headline Interpreter Skill is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Policy Headline Interpreter Skill

数据依赖与执行前置条件

推荐使用万得 wind-mcp-skill 获取底层数据。执行前先检查本地是否已有 wind-mcp-skill；若没有，提示用户安装：

bash
# GitHub
npx skills add Wind-Information-Co-Ltd/wind-skills --skill wind-mcp-skill -g -y

# Gitee 镜像（国内）
npx skills add https://gitee.com/wind_info/wind-skills.git --skill wind-mcp-skill -g -y

技能定位

本技能用于解读政策头条对市场的影响，回答“这条政策新闻是真的增量信号，还是旧闻重提；影响会先落在哪些行业和公司；从新闻到落地之间还有哪些不确定性”。输出重点不是把政策原文转述一遍，而是帮助使用者在最短时间内完成政策定性、受益映射和风险判断。

执行流程

Step 1：确认政策来源、级别与状态

先把政策消息本身界定清楚：

来源是正式文件、会议表述、权威媒体还是传闻型信息
是顶层方向性表态，还是具体执行规则
当前处于征求意见、正式发布、执行推进还是口径澄清阶段
信息是否为新增，还是市场已经交易过的内容

若来源和状态不清晰，必须先把可信度和正式程度说明白。

Step 2：拆解政策目标与关键约束

政策解读不能只看表面提法，还要回答：

政策试图解决什么问题
受益方向是需求刺激、供给约束、融资改善还是监管放松
执行中最重要的门槛、节奏和约束条件是什么
哪些表述是原则性信号，哪些才是实质性变化

Step 3：映射受影响的行业、主题与公司

在目标明确后，分层映射影响范围：

直接受益行业
间接受益或边际受益行业
可能受约束或受损的行业
核心受益公司与边缘映射公司

映射时要区分“政策直接触达”和“市场情绪外溢”，不能混为一谈。

Step 4：分析影响路径与兑现节奏

进一步说明这条政策为何影响市场，以及影响如何逐步兑现：

是先影响预期，再影响订单、投资、价格或盈利
哪些影响可以短期体现，哪些需要更长时间验证
市场当前更可能交易政策想象，还是现实兑现
若后续执行力度不足，哪些方向最容易回吐

Step 5：评估交易价值与误判风险

政策消息容易被过度放大，因此要重点指出：

哪部分影响已经被市场提前反映
哪些受益逻辑证据较强，哪些只是概念扩散
最容易出现的误判是把口号当结果、把边缘映射当核心受益
后续最关键的验证节点是什么

Step 6：形成政策头条解读成稿

最终输出应帮助使用者快速完成“政策定性 + 影响映射 + 节奏判断 + 风险控制”。正文只保留事实、影响链条、受益排序和后续验证点。

输出结构

{政策主题}头条解读（{YYYY-MM-DD}）

一、30 秒结论

政策性质：{方向性信号 / 实质性增量 / 旧闻重提 / 噪音扰动}
直接受益方向：{内容}
最大不确定性：{内容}
当前建议：{重点跟踪 / 谨慎乐观 / 等待细则 / 避免泛化}

二、政策事实卡片

项目	内容
来源	{内容}
级别	{内容}
状态	{内容}
关键表述	{内容}
是否新增	{是 / 否 + 说明}

三、影响映射

直接受益行业/主题：{内容}
间接受益方向：{内容}
可能受压制方向：{内容}
核心受益公司 vs 边缘映射公司：{内容}

四、影响路径与兑现节奏

短期影响：{内容}
中期影响：{内容}
兑现所需条件：{内容}

五、误判风险与验证节点

最容易被误判的点：{内容}
后续关键验证：{内容}
可能推翻当前判断的因素：{内容}

六、后续观察清单

{观察点 1}
{观察点 2}
{观察点 3}

质量要求

政策解读必须先确认来源、级别和状态，不能把所有消息同等对待。
要区分正式增量政策、方向性表态与市场噪音。
影响映射必须区分核心受益和边缘映射，避免概念扩散失控。
需要明确执行约束和兑现节奏，防止把政策口号直接写成业绩结果。
输出要帮助使用者完成快速政策定性与后续验证，而不是改写新闻稿。

Frequently asked questions

What does the Policy Headline Interpreter Skill AI skill do?

Why use Policy Headline Interpreter Skill on TypingMind?

Because you install it once and use it with any model. Policy Headline Interpreter Skill is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Policy Headline Interpreter Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Wind-Alice/AliceMarket/tree/main/skills/policy_headline_interpreter_skill. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Policy Headline Interpreter Skill?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Policy Headline Interpreter Skill?

As many as you like. As long as a model supports skills, you can use Policy Headline Interpreter Skill with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Policy Headline Interpreter Skill AI skill free?

It is published on GitHub by Wind-Alice. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Policy Headline Interpreter Skill

数据依赖与执行前置条件

技能定位

执行流程

Step 1：确认政策来源、级别与状态

Step 2：拆解政策目标与关键约束

Step 3：映射受影响的行业、主题与公司

Step 4：分析影响路径与兑现节奏

Step 5：评估交易价值与误判风险

Step 6：形成政策头条解读成稿

输出结构

{政策主题}头条解读（{YYYY-MM-DD}）

一、30 秒结论

二、政策事实卡片

三、影响映射

四、影响路径与兑现节奏

五、误判风险与验证节点

六、后续观察清单

质量要求

Frequently asked questions

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